Alpha Insure will use Akur8’s RISK, RATE, and DEMAND modules to enhance its pricing processes.
According to the insurtech, Akur8’s platform automates risk modeling through proprietary transparent machine learning technology, enabling pricing teams to make faster and more informed decisions. Key benefits include increased predictive performance, accelerated time-to-accuracy, and full transparency and control over model creation.
Alpha Insure, founded in 2004, has grown from a short-term insurance administrator to a key player in the South African market, with an annual Gross Written Premium (GWP) approaching 2 billion Rand. The company offers a broad range of personal and commercial insurance products.
By implementing Akur8’s cloud-based pricing platform for its Property & Casualty business, Alpha Insure aims to position itself for continued growth and development.
“We are excited to begin this new journey with Alpha Insure in South Africa. Two years after we entered the market, this fourth collaboration with a South African Insurer solidifies our position as the leading provider of pricing software for the insurance industry in the region,” said Samuel Falmagne, CEO at Akur8.
James Reid, Actuarial Executive at Alpha Insure, also commented, saying: “We had an excellent experience during our trial period with Akur8. The platform streamlined every modeling step required, offering an intuitive, user-friendly interface that empowers us to interpret models effectively and make adjustments with ease.”
He continued: “We achieved exceptional results in risk model performance, gaining clear visibility into variables and their corresponding coefficients. The platform’s statistical analysis capabilities enabled us to model effectively, even on thin data sets, with transparent indicators of model reliability. Akur8 also streamlined post-modeling analysis, making it easy to build and compare rating models against current pricing strategies, and precisely identify affected populations.”
Reid added: “The overall process, from data upload to variable selection and statistical examination, proved to be quick and highly efficient, underscoring the platform’s usability and robust functionality.”
